Abstract: Equilibrium climate sensitivity (ECS) is a key predictor of climate change.
However, it is not very well constrained, either by climate models or by
observational data. The reasons for this include strong internal variability
and forcing on many time scales. In practise this means that the 'equilibrium'
will only be relative to fixing the slow feedback processes before comparing
palaeoclimate sensitivity estimates with estimates from model simulations. In
addition, information from the late Pleistocene ice age cycles indicates that
the climate cycles between cold and warm regimes, and the climate sensitivity
varies considerably between regime because of fast feedback processes changing
relative strength and time scales over one cycle.
In this paper we consider climate sensitivity for quite general climate
dynamics. Using a conceptual Earth system model of Gildor and Tziperman (2001)
(with Milankovich forcing and dynamical ocean biogeochemistry) we explore
various ways of quantifying the state-dependence of climate sensitivity from
unperturbed and perturbed model time series. Even without considering any
perturbations, we suggest that climate sensitivity can be usefully thought of
as a distribution that quantifies variability within the 'climate attractor'
and where there is a strong dependence on climate state and more specificially
on the 'climate regime' where fast processes are approximately in equilibrium.
We also consider perturbations by instantaneous doubling of CO$_2$ and
similarly find a strong dependence on the climate state using our approach.